The number of passengers in an elevator car is frequently employed as a key factor in methods of dispatching elevator cars to provide most effective service to the passengers. Typical examples are determining if a large number of passengers are leaving the lobby floor during the morning rush hour, in which case an up-peak mode of dispatching would be initiated; similarly with respect to downwardly traveling passengers arriving at the lobby floor during the evening rush hour, which may invoke a down-peak mode of dispatching. An example can be found in U.S. patent application Serial No. 07/879,558 filed on May 4, 1992 by Sirag and Weisser, entitled "Using Fuzzy Logic to Determine the Traffic Mode of an Elevator System". In said application, the number of passengers is determined using fuzzy logic in a manner which is described therein, and which is also described and claimed in a commonly owned, co-pending U.S. patent application Ser. No. 07/879,528 filed on May 4, 1992 of Sirag, entitled "Using Fuzzy Logic to Determine the Number of Passengers in an Elevator Car" (both applications are incorporated herein by reference). That method utilizes a large amount of data indicative of the variations in weight which various numbers of people (such as two people, eleven people, twenty-eight people) might weigh in a given elevator system. The data can be obtained empirically by simply observing the number of people in an elevator car and recording that number with the weight indicated by the elevator load weighing system at that time. After collecting large amounts of data, the various weights for any given passenger count can be strung together to form a fuzzy set in which each basis element is a discernible weight for the elevator and the membership for each basis element is dependent on the number of times (normalized) that such weight has been observed. Then, to use the data, for any given weight, a fuzzy set is established which is the membership for that weight basis element within each of the fuzzy sets relating to all possible numbers of passengers. Thus, a slice through those fuzzy sets representing weights for numbers of passengers, results in a single fuzzy set of passengers for a given weight, in which each basis element is a number of passengers and the membership of that basis element is the relative likelihood that that number of passengers will result in the given weight of the set.
There are other ways to determine the number of people in an elevator car, particularly those that use discrete people counters, such as infrared and video techniques of which many are known. However, these can be quite expensive and still are not absolutely foolproof in terms of providing an absolutely accurate count of the number of people that enter or leave an elevator car. In the methodology of the aforementioned Sirag application, if suitable information is acquired empirically, it must present a very accurate prediction of the average number of people at a given weight. On the other hand, the discrete people counters are more likely to present actual rather than average data, but they have been shown to be inaccurate (e.g., missing some passengers; counting baggage as a passenger).
In the aforementioned parent application (which is incorporated herein by reference), the fact that the difference in weight between male and female passengers can significantly affect the accuracy of fuzzy sets which represent an average number of passengers is accommodated by providing separate fuzzy sets indicative of the number of male passengers which might cause a given elevator car load weight, and fuzzy sets of female passengers which might cause a given elevator car load weight, and ratioing each of those fuzzy sets in accordance with the proportionate share of male and female populations within the building. The union of these two fuzzy sets provides a more accurate determination of the likely number of a mix of male and female passengers within the building than the fuzzy sets of average numbers of passengers which has heretofore been utilized in the prior art.